Condition monitoring and severity estimation of rotor demagnetisation fault using magnetic flux measurement data

Abstract This article studies and investigate the magnetic characteristics of a surface mounted permanent magnet (SPM)‐type brushless direct current (BLDC) motor when subjected to demagnetisation fault conditions. The proposed research subjugates the limitation of estimating the State of Health (SoH...

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Autores principales:	Adil Usman, Vivek. K. Sharma, Bharat. S. Rajpurohit
Formato:	article
Lenguaje:	EN
Publicado:	Wiley 2021
Materias:	Production of electric energy or power. Powerplants. Central stations TK1001-1841 Energy industries. Energy policy. Fuel trade HD9502-9502.5
Acceso en línea:	https://doaj.org/article/d4522f462e51423697c26c2a7f398b5d
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spelling	oai:doaj.org-article:d4522f462e51423697c26c2a7f398b5d2021-11-11T13:07:32ZCondition monitoring and severity estimation of rotor demagnetisation fault using magnetic flux measurement data2516-840110.1049/esi2.12024https://doaj.org/article/d4522f462e51423697c26c2a7f398b5d2021-12-01T00:00:00Zhttps://doi.org/10.1049/esi2.12024https://doaj.org/toc/2516-8401Abstract This article studies and investigate the magnetic characteristics of a surface mounted permanent magnet (SPM)‐type brushless direct current (BLDC) motor when subjected to demagnetisation fault conditions. The proposed research subjugates the limitation of estimating the State of Health (SoH) of a BLDC motor drive when deployed in electric vehicle (EV) applications. Demagnetisation faults adversely affect the performance of a machine and indirectly the EV drive system, bringing significant transformation in the machine’s characteristics and quantities. The novel method of measuring the radial magnetic field (Bg) across the machine airgap assists in diagnosing and estimating the % severity of faults under the subjected fault conditions. A numerical co‐simulation‐based model of a BLDC motor is developed to investigate the performance of the machine under both healthy and fault conditions. The BLDC motor being studied is operated using a field programmable gate array (FPGA) based control drive adopting a hysteresis current control (HCC) technique. The experimental investigation of a complete BLDC motor test drive is carried out with an FPGA‐based algorithm developed on the Xilinx ISE tool. The outcomes obtained are validated with the numerical results obtained through a finite element (FE) analysis. The proposed study uses a fluxgate sensor for experimental measurement of the flux density of a BLDC motor drive, which is vital for estimating the fault severity and scheduling the maintenance accordingly. The experimental investigations are found to be in validation with the proposed techniques in estimating the health of a BLDC motor‐driven EV drive system.Adil UsmanVivek. K. SharmaBharat. S. RajpurohitWileyarticleProduction of electric energy or power. Powerplants. Central stationsTK1001-1841Energy industries. Energy policy. Fuel tradeHD9502-9502.5ENIET Energy Systems Integration, Vol 3, Iss 4, Pp 437-450 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Production of electric energy or power. Powerplants. Central stations TK1001-1841 Energy industries. Energy policy. Fuel trade HD9502-9502.5
spellingShingle	Production of electric energy or power. Powerplants. Central stations TK1001-1841 Energy industries. Energy policy. Fuel trade HD9502-9502.5 Adil Usman Vivek. K. Sharma Bharat. S. Rajpurohit Condition monitoring and severity estimation of rotor demagnetisation fault using magnetic flux measurement data
description	Abstract This article studies and investigate the magnetic characteristics of a surface mounted permanent magnet (SPM)‐type brushless direct current (BLDC) motor when subjected to demagnetisation fault conditions. The proposed research subjugates the limitation of estimating the State of Health (SoH) of a BLDC motor drive when deployed in electric vehicle (EV) applications. Demagnetisation faults adversely affect the performance of a machine and indirectly the EV drive system, bringing significant transformation in the machine’s characteristics and quantities. The novel method of measuring the radial magnetic field (Bg) across the machine airgap assists in diagnosing and estimating the % severity of faults under the subjected fault conditions. A numerical co‐simulation‐based model of a BLDC motor is developed to investigate the performance of the machine under both healthy and fault conditions. The BLDC motor being studied is operated using a field programmable gate array (FPGA) based control drive adopting a hysteresis current control (HCC) technique. The experimental investigation of a complete BLDC motor test drive is carried out with an FPGA‐based algorithm developed on the Xilinx ISE tool. The outcomes obtained are validated with the numerical results obtained through a finite element (FE) analysis. The proposed study uses a fluxgate sensor for experimental measurement of the flux density of a BLDC motor drive, which is vital for estimating the fault severity and scheduling the maintenance accordingly. The experimental investigations are found to be in validation with the proposed techniques in estimating the health of a BLDC motor‐driven EV drive system.
format	article
author	Adil Usman Vivek. K. Sharma Bharat. S. Rajpurohit
author_facet	Adil Usman Vivek. K. Sharma Bharat. S. Rajpurohit
author_sort	Adil Usman
title	Condition monitoring and severity estimation of rotor demagnetisation fault using magnetic flux measurement data
title_short	Condition monitoring and severity estimation of rotor demagnetisation fault using magnetic flux measurement data
title_full	Condition monitoring and severity estimation of rotor demagnetisation fault using magnetic flux measurement data
title_fullStr	Condition monitoring and severity estimation of rotor demagnetisation fault using magnetic flux measurement data
title_full_unstemmed	Condition monitoring and severity estimation of rotor demagnetisation fault using magnetic flux measurement data
title_sort	condition monitoring and severity estimation of rotor demagnetisation fault using magnetic flux measurement data
publisher	Wiley
publishDate	2021
url	https://doaj.org/article/d4522f462e51423697c26c2a7f398b5d
work_keys_str_mv	AT adilusman conditionmonitoringandseverityestimationofrotordemagnetisationfaultusingmagneticfluxmeasurementdata AT vivekksharma conditionmonitoringandseverityestimationofrotordemagnetisationfaultusingmagneticfluxmeasurementdata AT bharatsrajpurohit conditionmonitoringandseverityestimationofrotordemagnetisationfaultusingmagneticfluxmeasurementdata
_version_	1718439079903756288

Condition monitoring and severity estimation of rotor demagnetisation fault using magnetic flux measurement data

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